1	Course Title:	ALGORITHMS
2	Course Code:	BM5103
3	Type of Course:	Compulsory
4	Level of Course:	Second Cycle
5	Year of Study:	1
6	Semester:	1
7	ECTS Credits Allocated:	6
8	Theoretical (hour/week):	3
9	Practice (hour/week) :	0
10	Laboratory (hour/week) :	0
11	Prerequisites:	none
12	Recommended optional programme components:	None
13	Language:	Turkish
14	Mode of Delivery:	Face to face
15	Course Coordinator:	Prof. Dr. PINAR KIRCI
16	Course Lecturers:	yok
17	Contactinformation of the Course Coordinator:	Bilgisayar müh. bölüm binası 1. kat oda 110 pinarkirci@uludag.edu.tr
18	Website:
19	Objective of the Course:	The goal of this course is to introduce students the advanced techniques for algorithm analysis and design.
20	Contribution of the Course to Professional Development	The goals of this course are to study several fundemantal algorithms which are used to solve conventional computational problems and to introduce some mathematical methods and tools that are useful in the analysis of algorithms.

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Learning Outcomes:

1 Students should develop proficiency in fundamental algorithmic techniques and analysis as well as the ability to implement the algorithms in a programming language.; 2 they should understand computational limitations such as NP-completeness, and how to tackle such real-world algorithmic problems via randomized and approximation techniques.;

22	Course Content:

Week	Theoretical	Practical
1	Asymptotic Notation, Divide and Conquer Method
2	Overview of Sorting Algorithms : Insertion Sort, Quicksort, Merge Sort, Heapsort
3	Dynamic Programming : Rod Cutting Problem, Longest Common Subsequence Problem
4	Greedy Algorithms
5	B-Trees
6	Fibonacci Heaps
7	Graph Algorithms I : Breadth-first Search, Depth-First Search
8	Graph Algorithms II : Minimum Spanning Trees, Shortest Path Algorithms
9	Graph Algorithms III : Maximum Flow Problem
10	Multithreaded Algorithms : Matrix Multiplication, Merge Sort
11	Multithreaded Algorithms : Matrix Multiplication, Merge Sort
12	Number-Theoretic Algorithms : Extended Euclid Algorithm, Miller-Rabin Primality Test, Integer Factorization
13	String Matching Algorithms
14	Computational Geometric Algorithms : Line Segment Algorithms, Finding the Closest Pair of Points

23	Textbooks, References and/or Other Materials:	- Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein, Introduction To Algorithms, 3rd ed, The MIT Press, 2009. - Michael T. Goodrich, Roberto Tamassia,Algorithm Design : Foundations, Analysis and Internet Examples, John Wiley & Sons Inc., 2002. Cormen, Leiserson, Rivest, and Stein. Introduction to Algorithms.
24	Assesment

TERM LEARNING ACTIVITIES	NUMBER	PERCENT
Midterm Exam	1	50
Quiz	0	0
Homeworks, Performances	0	0
Final Exam	1	50
Total	2	100
Contribution of Term (Year) Learning Activities to Success Grade		50
Contribution of Final Exam to Success Grade		50
Total		100
Measurement and Evaluation Techniques Used in the Course	written exam
Information

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ECTS / WORK LOAD TABLE

Activites	NUMBER	TIME [Hour]	Total WorkLoad [Hour]
Theoretical	14	3	42
Practicals/Labs	0	0	0
Self Study and Preparation	14	2	28
Homeworks, Performances	0	0	0
Projects	0	0	0
Field Studies	0	0	0
Midtermexams	1	50	50
Others	0	0	0
Final Exams	1	60	60
Total WorkLoad			230
Total workload/ 30 hr			6
ECTS Credit of the Course			6

26	CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS
PQ1 PQ2 PQ3 PQ4 PQ5 PQ6 LO1 3 4 1 1 1 1 LO2 1 1 3 1 1 1

LO: Learning Objectives

PQ: Program Qualifications

Contribution Level:

1 Very Low

2 Low

3 Medium

4 High

5 Very High